CN112163789B - Teacher workload evaluation system and method for online education - Google Patents
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Abstract
The invention provides a teacher workload evaluation system for online education.A document identification module 1 reads documents uploaded by a teacher one by one and judges the type of the documents according to file header information or extension. The element extraction module 11, the complexity calculation module 12, and the 1 st workload calculation module 13 calculate the workload (first workload) of the office document. The frame number/duration analysis module 21 and the 2 nd workload calculation module 22 calculate the workload (2 nd workload). The text analysis module 31, the knowledge point/chapter number statistic module 32, and the 3 rd workload calculation module 33 calculate the workload (3 rd workload). And the comprehensive evaluation module 2 counts the 1 st, 2 nd and 3 rd workloads by taking a teacher as a unit.
Description
Technical Field
The present invention relates to teacher workload evaluation systems and methods for online education, and more particularly, to quantitative evaluation of teacher workload.
Background
With the rapid development of internet and online education, intelligent teaching is developed in many schools. Through the intelligent teaching platform, a teacher can prepare lessons collectively, give tutoring for teaching, conduct network operation, annotate on line, read examination automatically and the like, and therefore unified teaching management and resource sharing are achieved. Through wisdom teaching platform, the student can look up and lead this, the teaching and assisting material, network operation etc. of learning, can also listen teacher's explanation, and teacher's interdynamic.
The use of wisdom teaching platform provides very big facility for the school, has improved the quality of teaching to a certain extent, but has also caused the impact to traditional teacher management mode. As with traditional classroom teaching, online education also requires on-duty teachers to build archives, record the professional development data of the teachers, and formulate a teacher promotion system. Aiming at teachers in different levels, different training courses with different emphasis points are designed, and the education quality and level are continuously improved. All the tasks relate to the evaluation of the workload of the teachers, but the existing teaching platforms lack the function of evaluating the workload of the teachers. Especially, the workload evaluation is performed by taking documents uploaded by teachers, such as office documents or audio and video documents, which relates to the complexity of the documents and the time cost for making the documents, and the actual workload of the teachers cannot be effectively calculated without considering the factors.
The invention aims to provide an evaluation system and an evaluation method which can quantify the complexity or the time cost of a document and effectively calculate the workload of a teacher through quantification.
Disclosure of Invention
In order to achieve the above purpose, the invention provides the following technical scheme:
the first technical solution is 1. a teacher workload evaluation system for online education, characterized by comprising: a document identification module (1), an element extraction module (11), a complexity calculation module (12), a 1 st workload calculation module (13), a frame number/duration analysis module (21), a 2 nd workload calculation module (22), a text analysis module (31), a knowledge point/chapter number statistic module (32), a 3 rd workload calculation module (33) and a comprehensive evaluation module (2),
wherein, the document identification module (1) reads the documents uploaded by the teacher one by one, judges the document type according to the file head information or the extension and the content in the document, the document containing characters and other elements is a comprehensive document, the document only containing characters and numbers is a text document,
an element extraction module (11), a complexity calculation module (12) and a 1 st workload calculation module (13) calculate the 1 st workload of the integrated document,
the element extraction module (11) is used for extracting the total page number of the integrated document and elements in each page,
the complexity calculating module (12) carries out grouping statistics on the Element object array Element [ ] of the single page, counts the occurrence frequency of each Element in each page, calculates the complexity of each page,
the 1 st workload calculation module (13) calculates a weighted average through a grouping array according to the frequency and the number of pages of each element appearing on each page and the weight of each element, evaluates the manufacturing cost of the page, calculates the workload of a single page, calculates the 1 st workload of the integrated document according to the workload and the number of pages of the single page,
the frame number and time length analysis module (21) obtains the frame number and time length of the video by converting the document,
the 2 nd workload calculation module (22) calculates the 2 nd workload of the audio and video according to the frame number and the time length of the video, the frame number weight and the time length weight,
the text analysis module (31) analyzes the text by the words by using the knowledge point and chapter directory dictionary, extracts the information of the knowledge points and chapters and the number of characters appearing in the text content,
the text analysis module (31) extracts chapters and knowledge points appearing in the text by using the chapter data and the knowledge point dictionary and adopting a word segmentation algorithm,
a knowledge point/chapter number statistic module (32) counts the number of times of occurrence of the knowledge points and chapter information in the document,
a 3 rd workload calculation module (33) calculates the 3 rd workload of the text according to the knowledge point number, chapter number, character number, knowledge point weight, chapter weight, and character weight,
and the comprehensive evaluation module (2) takes a teacher as a unit and counts the 1 st, 2 nd and 3 rd workloads.
Preferably, the comprehensive evaluation module (2) normalizes the 1 st, 2 nd and 3 rd workloads to calculate the workload score of each teacher.
Preferably, the integrated document is an office document or a WPS document, including any one or more of a word document, an Excel document, and a PowerPoint document.
The second technical scheme is a teacher workload evaluation method of online education, which is characterized by comprising the following steps of:
step S1 (step S10), the document identification module (1) reads the documents in the prescribed order and loads the documents,
step S2 (step S20), the document identification module (1) judges the document type according to the file head information, the extension name and the content in the document, the document containing words and other elements is a comprehensive document, only the words and numbers document is a text document,
in step S3 (step S32), the element extraction module (11) parses the integrated document, extracts the total number of pages of the document, each Page object array Page [ ],
step S4 (step 34), the Element extraction module (11) traverses the Page array, and for the single-Page object, respectively obtains all elements of the single Page to obtain an Element object array Element [ ],
step S5 (step 36), traverse all sub-elements of the element,
step S6 (step S38), the complexity calculating module (12) carries out grouping statistics on the Element object array Element [ ] of the single page, counts the frequency of each Element appearing on each page, calculates the complexity of each page, the 1 st workload calculating module (13) calculates the weighted average through the grouping array according to the frequency and the number of the each Element appearing on each page and the weight of each Element, evaluates the manufacturing cost of the page, calculates the workload of the single page, calculates the 1 st workload of the integrated document according to the workload and the number of the single page,
in step S7 (step S42), the frame number/time length analysis module 21 processes the document to extract the frame number and time length information of the video,
step S8 (step S44), the 2 nd workload calculation module (22) calculates the 2 nd workload of the video according to the frame number and the duration information,
step S9 (step S52), the text parsing module 31 counts the number of characters of the text,
step S10 (step 54), the text analysis module 31 loads chapter data and a knowledge point dictionary, extracts chapters and knowledge points appearing in the text by using a word segmentation algorithm,
in step S11 (step S56), the knowledge point/chapter number statistic module 32 counts the number of occurrences of the knowledge point and chapter information in the document,
step S12 (step S58), the 3 rd workload calculation module 33 calculates the 3 rd workload according to the knowledge point number, chapter number, character number and the weight of the knowledge point, chapter, character,
and step S13, the comprehensive evaluation module (2) takes a teacher as a unit and counts the 1 st, 2 nd and 3 rd workloads.
Preferably, in step S13, the comprehensive evaluation module (2) normalizes the 1 st, 2 nd, and 3 rd workloads to calculate the workload score of each teacher.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. In the drawings:
FIG. 1 is a system diagram of online education;
FIG. 2 is a block diagram of a workload evaluation module;
FIG. 3 is a flowchart of workload score calculation for a single document.
Detailed Description
The present invention provides many applicable inventive concepts that can be embodied in a wide variety of specific contexts. The specific examples described in the following embodiments of the present invention are merely illustrative of specific embodiments of the present invention and do not limit the scope of the invention.
Fig. 1 is a system explanatory diagram of online education. As shown in fig. 1, the teaching platform c is a cloud platform, and is composed of a server and software running on a computer as a main body of network teaching, and functionally includes a management module 300, a teaching material module 400, and a workload evaluation module 500. The teacher's end a and the student's segment b are connected to the teaching platform c via a network (e.g., the internet). The teacher uploads the compiled teaching book, teaching auxiliary materials and the like to the teaching material module 400 of the teaching platform c through the computer of the teacher end a, and the students operate the computer of the student end 6 according to the teaching requirements to perform online or offline learning or download the corresponding teaching materials from the teaching material module 400.
The management module 300 is used for managing the whole teaching platform, a teacher and students respectively input own names and passwords, the management module 300 authenticates the names and the passwords, and after the names and the passwords pass the authentication, the teacher and the students can enter the teaching platform to give lessons (document uploading) and study (document downloading).
The workload evaluation module 500 is configured to evaluate the workload of each teacher, that is, evaluate the workload of each teacher in a certain period, for example, the workload in one month, by performing a quantitative analysis on the complexity of uploading documents by the teacher.
Fig. 2 is a structural diagram of a workload evaluation module. As shown in fig. 2, the workload evaluation module 500 is composed of a plurality of sub-modules. The submodules in the present embodiment include a document identification module 1, an element extraction module 11, a complexity calculation module 12, a 1 st workload calculation module 13, a frame number/duration analysis module 21, a 2 nd workload calculation module 22, a text analysis module 31, a knowledge point/chapter number statistics module 32, a 3 rd workload calculation module 33, and a comprehensive evaluation module 2.
The document identification module 1 reads the documents uploaded by the teachers one by the teaching material module 400, and determines the document types according to the file header information or extension and the contents in the documents. The read documents are documents uploaded during the period of the calculation workload. In the present embodiment, workload evaluation is performed on documents in three formats, i.e., office documents, audio/video documents, and text documents. For convenience, in this embodiment, a document containing text and other elements such as a picture, a table, and text is simply referred to as an office document (integrated document), and the format of the document may be word, Excel, PowerPoint, and the like. The audio-video may be in various formats, such as h.261. Text is simply referred to as text, for example in TXT format, for text-only text and numeric documents.
If the document identification module 1 identifies an office document, that is, the document contains characters and other elements such as pictures, tables, characters, etc., the workload (first workload) of the office document is calculated by the element extraction module 11, the complexity calculation module 12, and the 1 st workload calculation module 13.
The calculation target of the 1 st workload is not limited to the office document, and may be an integrated document in which a plurality of elements such as figures and characters are prepared.
The element extraction module 11 is configured to extract the total number of pages of the office document and elements in each page, for example, parsing the document through a library office or an aspose office tool, and extracting the total number of pages and elements such as graphic shapes, pictures, text boxes, animations, and characters.
Due to the fact that workload cost of manufacturing of each element is different, the times of appearance of different elements in a single page can be distinguished through the processing, and workload calculation is carried out accurately.
The complexity calculating module 12 calculates the complexity of each page of the document by the following formula
Wherein Wi Page j elementIs the weight of each element j, and the value is obtained according to experience or by investigation. For example, the time it takes for several teachers to individually make single element documents, such as graphic shapes, pictures, text, animated documents, is evaluated based on school practice. And (4) obtaining the median according to the time spent sequencing, wherein the value range is 0-1. Weight WElement jThe calculation method of (2) is as follows:
Welement j= TElement j /∑ TElement k
The number of elements in the same page is large, so that the page is rich (complex) and the work load paid by teachers is large.
The 1 st workload calculation module 13 calculates the workload T of the entire office document by the following equationj document。
Tj document= ∑Cj document i Page*Nj number of pages of document
Wherein, Cj document i PageIs the complexity of each page of the document j, obtained by the complexity calculation module 12, NjIs the total number of pages of the document.
After calculating the workload scores of all office documents, the 1 st workload calculation module 13 calculates the workload T of each teacher in units of teachers by the following formulai teacher(1 st workload).
Ti teacher= ∑Ci teacher j document
The 1 st workload calculation module 13 obtains a workload score (1 st workload score) of each teacher through normalization processing based on the workload (1 st workload) of each teacher.
If the document recognition module 1 recognizes that the document is an audio/video document, the frame number/duration analysis module 21 and the 2 nd workload calculation module 22 calculate the workload (2 nd workload).
The frame number/duration analysis module 21 analyzes the converted document by, for example, ffmpeg, and acquires the frame number and duration of the video.
The 2 nd workload calculation module 22 calculates the workload of the audio and video according to the following equation.
Vi teacherAnd (= w1 × frame + w2 × duration, wherein w1 and w2 are weighted values. w1 and w2 are generally given empirically and are calculated as 1:1 of equal importance in this embodiment.
After calculating the workload of all audios and videos, the 2 nd workload calculation module 22 calculates the workload (2 nd workload) of each teacher in units of teachers. And then, according to the workload (2 nd workload) of each teacher for making audios and videos, obtaining the workload score (2 nd workload score) of each teacher for making audios and videos through normalization processing.
If the document recognition module 1 recognizes that the document is a text document, that is, if only words and numbers are contained in the document, the workload (3 rd workload) is calculated by the text parsing module 31, the knowledge point/chapter number counting module 32, and the 3 rd workload calculating module 33.
The text parsing module 31 parses the text by words using the knowledge point and chapter directory dictionary, and extracts the knowledge point and chapter information and the number of characters appearing in the text content.
The knowledge point/chapter number counting module 32 counts the number of times the knowledge point and chapter information appear in the document.
The 3 rd workload calculation module 33 calculates workload scores for the respective teachers according to the following equation.
Ri teacher= w1 knowledge points + w2 chapter number + w3 character number, where w1, w2, w3 are weight values. w1, w2 and w3 are given according to experience, and the number of times of the knowledge points is large in general, which shows that the content covered by the teacher has wider knowledge points and higher importance of the knowledge points. In the present embodiment, w 1: w 2: w3= 100: and (5) calculating by 100: 2.
After calculating the workload of all texts, the 3 rd workload calculation module 33 calculates the workload (the 3 rd workload) for each teacher to create a text by taking the teacher as a unit, and obtains the workload score (the 3 rd workload score) for each teacher to create a text by normalization processing.
The comprehensive evaluation module 2 synthesizes the workload scores of the various teachers for making the offine documents, audios and videos and texts, and calculates the workload scores of the various teachers according to a certain weight.
The calculation of the workload of a single document is explained below by means of the flowchart of fig. 3.
In step 10, the document identification module 1 reads the documents in a prescribed order from the data module 400 and loads the documents.
In step 20, the document identification module 1 obtains the document type according to the file header information, the extension name and the content in the document.
In step 30, the document identification module 1 determines whether the document is an office document, and "Yes" proceeds to step 32, and calculates the workload for creating the office document (1 st workload), and "No" proceeds to step 40, and further determines whether the document is a video.
If the judgment result in the step 40 is "Yes", the step 42 is entered to calculate the workload (2 nd workload) for making audio/video, and "No" is entered to the step 50 to judge whether the document is a text.
If the result of the determination in step 50 is "Yes", the process proceeds to step 52, where the workload for creating a text (No. 3) and "No" are calculated, and the document is an out-of-specification document, and the workload calculation for the document is terminated.
In step 32, the element extraction module 11 analyzes the document using an office tool (e.g. library office or aspose office), and extracts the total number of pages of the document, and each Page object array Page [ ].
In step 34, the Element extraction module 11 traverses the Page array, and for a single-Page object, acquires all elements of the single Page respectively to obtain an Element object array Element [ ]. Such as text, tables, audio-visual, graphical shapes, pictures, text boxes, formulas, and the like.
The data of the following table, which contains the element types and the occurrence frequencies of the single pages in the table and the weights of the calculation workload, are obtained through grouping statistics, for example.
The 1 st workload statistical module 13 calculates a weighted average by grouping arrays, evaluates the manufacturing cost of the page, and calculates the workload of a single page. For example, the single page workload scores in the table above are:
= SUM (frequency of occurrence of element. weight)
=50*0.01+5*0.15+1*0.4+10*0.05+5*0.05+5*0.05+6*0.29
=0.5+0.75+0.4+0.5+0.25+0.25+1.74=4.39。
In step 42, the frame number/duration analysis module 21 performs FFmpeg processing on the document to extract the frame number and duration information of the video.
In step 44, the 2 nd workload calculation module 22 calculates the workload of the video according to the frame number and the duration information.
The audio and video workload (2 nd workload) = frame number weight + frame weight + duration weight, and the higher the score is, the larger the workload for making the audio and video is.
In step 52, the text parsing module 31 counts the number of words (number of characters) of the text.
In step 58, the 3 rd workload calculation module 33 calculates the workload of creating the text according to the following formula.
Text workload = w1 knowledge points + w2 chapter number + w3 character number, where w1, w2, and w3 are weights of knowledge points, chapters, and character numbers, respectively.
The above description has been made on the processing procedure of a single document, and after the calculation of the workload of the document is finished, the next document is read and the above steps are repeated until the workload of all documents within a specified period is calculated.
The workload of the office document is explained below.
For example, there are three documents in the following table, one document has one page, the single page workload is 5, and the entire shaddock workload is 5; the second document has 5 pages, the workload of each page is 2, 3, 4 and 1 respectively, and the workload of the whole document is 15; the third document has three pages, the workload of each page is 6, 8 and 4 respectively, and the workload of the whole document is 18.
The following table shows the workload of three videos with different frame numbers and durations. The frame number weight and the duration weight are, for example, 1: 1. the workload of each audio/video is respectively 42.5, 65 and 90.
The following table is the workload situation for the text. Chapter number, weight of knowledge point is 1: 100: 100. the workload of the three documents is 13.4, 23.3 and 7.4 by calculation.
The calculation of the workload score by each teacher will be described below.
Through the above steps, after the workload of all the documents in a predetermined period is calculated, the workload of each teacher is evaluated.
Because different classification scores have larger difference, each classification is normalized for convenience of processing.
The following table shows the office documents, audio/video and text workload of three teachers. The weights of the office document, the audio and video and the text are obtained through test evaluation in advance. In the present embodiment, 1: 1: 1.
is subjected to normalization processing to obtain
The score after normalization is a composite score of teacher score one. The teacher first workload is scored to be 0.22, the teacher second workload is scored to be 0.42, and the teacher third workload is scored to be 0.36, wherein the higher the score is, the larger the workload is.
The embodiment of the invention is explained above, and the invention can quantitatively analyze the complexity of the document and correctly and effectively evaluate the workload of teachers.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. For example, the document format is not limited to office documents, and may be documents in various formats such as WPS as long as the documents include a plurality of elements that affect the workload. The text for calculating the 3 rd workload is not limited to the document format, and may be documents of various formats.
Claims (5)
1. A teacher workload evaluation system of online education, characterized by comprising: a document identification module (1), an element extraction module (11), a complexity calculation module (12), a 1 st workload calculation module (13), a frame number/duration analysis module (21), a 2 nd workload calculation module (22), a text analysis module (31), a knowledge point/chapter number statistic module (32), a 3 rd workload calculation module (33) and a comprehensive evaluation module (2),
wherein, the document identification module (1) reads the documents uploaded by the teacher one by one, judges the document type according to the file head information or the extension and the content in the document, the document containing characters and other elements is a comprehensive document, the document only containing characters and numbers is a text document,
an element extraction module (11), a complexity calculation module (12) and a 1 st workload calculation module (13) calculate the 1 st workload of the integrated document,
the element extraction module (11) is used for extracting the total page number of the integrated document and elements in each page,
the complexity calculating module (12) carries out grouping statistics on the Element object array Element [ ] of the single page, counts the occurrence frequency of each Element in each page, calculates the complexity of each page,
the 1 st workload calculation module (13) calculates a weighted average through a grouping array according to the frequency and the number of pages of each element appearing on each page and the weight of each element, evaluates the manufacturing cost of the page, calculates the workload of a single page, calculates the 1 st workload of the integrated document according to the workload and the number of pages of the single page,
the frame number and time length analysis module (21) obtains the frame number and time length of the video by converting the document,
the 2 nd workload calculation module (22) calculates the 2 nd workload of the audio and video according to the frame number and the time length of the video, the frame number weight and the time length weight,
the text analysis module (31) analyzes the text by the words by using the knowledge point and chapter directory dictionary, extracts the information of the knowledge points and chapters and the number of characters appearing in the text content,
the text analysis module (31) extracts chapters and knowledge points appearing in the text by using the chapter data and the knowledge point dictionary and adopting a word segmentation algorithm,
a knowledge point/chapter number statistic module (32) counts the number of times of occurrence of the knowledge points and chapter information in the document,
a 3 rd workload calculation module (33) calculates the 3 rd workload of the text according to the knowledge point number, chapter number, character number, knowledge point weight, chapter weight, and character weight,
and the comprehensive evaluation module (2) takes a teacher as a unit and counts the 1 st, 2 nd and 3 rd workloads.
2. A teacher workload evaluation system of online education as recited in claim 1, wherein: and the comprehensive evaluation module (2) is used for carrying out normalization processing on the 1 st, the 2 nd and the 3 rd workloads and calculating the workload scores of the teachers.
3. The teacher workload evaluation system of online education as recited in claim 2, wherein: the comprehensive document is an office document or a WPS document and comprises any one or more of a word document, an Excel document and a PowerPoint document.
4. A teacher workload evaluation method of online education is characterized by comprising the following steps:
in step S1, the document identification module (1) reads the documents in a prescribed order and loads the documents,
step S2, the document identification module (1) judges the document type according to the file head information, the extension name and the content in the document, the document containing characters and other elements is a comprehensive document, only the document containing characters and numbers is a text document,
in step S3, the element extraction module (11) parses the integrated document to extract the total Page number of the document, each Page object array Page [ ],
step S4, the Element extraction module (11) traverses the Page [ ] array, and for the single Page [ ] object, respectively obtains all the elements of the single Page, and obtains the Element object array Element [ ],
step S5, traverse all sub-elements of the element,
step S6, the complexity calculating module (12) carries out grouping statistics on the Element object array Element [ ] of the single page, the frequency of each Element appearing in each page is counted, the complexity of each page is calculated, the 1 st workload calculating module (13) calculates the weighted average through the grouping array according to the frequency and the number of the each Element appearing in each page and the weight of each Element, the manufacturing cost of the page is evaluated, the workload of the single page is calculated, the 1 st workload of the comprehensive document is calculated according to the workload and the number of the single page,
in step S7, the frame number/duration analysis module 21 processes the document to extract the frame number and duration information of the video,
in step S8, the 2 nd workload calculation module (22) calculates the 2 nd workload of the video according to the frame number and the duration information,
in step S9, the text parsing module 31 counts the number of characters of the text,
step S10, the text analysis module (31) loads chapter data and a knowledge point dictionary, adopts a word segmentation algorithm to extract chapters and knowledge points appearing in the text,
in step S11, a knowledge point/chapter number statistic module (32) counts the number of times of occurrence of the knowledge points and chapter information in the document,
in step S12, the 3 rd workload calculation module (33) calculates the 3 rd workload according to the knowledge point number, chapter number, character number and the weight of the knowledge point, chapter, character,
and step S13, the comprehensive evaluation module (2) takes a teacher as a unit and counts the 1 st, 2 nd and 3 rd workloads.
5. The teacher workload evaluation method of online education as recited in claim 4, wherein: in step S13, the comprehensive evaluation module (2) normalizes the 1 st, 2 nd, and 3 rd workloads to calculate a workload score for each teacher.
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